Sociology 202
Research Principles and
Practice
Bogardus Social Distance Scale

Let’s say you’re interested in the extent to which non-Muslim
Canadian citizens are willing to associate with, say, Muslims.
You might ask the following questions:
1.
Are you willing to permit Muslims to live in your country?
Are you willing to permit Muslims to live in your community?
Are you willing to permit Muslims to live in your
neighbourhood?
Would you be willing to let a Muslim live next door to you?
Would you let your child marry a Muslim?
2.
3.
4.
5.
Objectives


To introduce the logic and skills of social
scientific research.
To develop a critical understanding in
consuming research.
Note: The importance in formulating social policy
(e.g., health care)
Overview of Course
Human Inquiry
vs.

Relies on common
sense

Tradition

Authority

Faith
Science
 Observation
 Logic
 Verifiable evidence
 Explicit procedures
 Replication
Common Errors in Human Inquiry




Overgeneralization
Inaccurate observation
Ego involvement in understanding
Premature closure of inquiry
Example: Letters to the editor
Aim of Systematic Empirical
Research




To observe (data collection)
Describe
Explain
Predict
The Research Process



Research is an integrated process.
It is made up of a series of sequential steps.
It builds on previous research.
Steps in the Research Process
1.
2.
Choose a topic or research interest. The
research topic should be clear and focused.
Review the literature.




What have other researchers done on the topic?
How did they do it?
What did they find?
Validity and reliability.
Steps in the Research Process
3.
Based upon the review of literature, refine/reformulate
your research topic.
Steps in the Research Process
4.
Deductive or inductive logic.
Types of Research
1.
Descriptive

2.
Exploratory

3.
What exists?
What is going on here?
Explanatory


Identify causes and effects of social phenomena
Predict how one phenomenon will change or vary in
response to variation in some other phenomenon.
Example: Testing hypotheses and theories.
Variables and Attributes

Variables are parts or aspects of reality that can
be seen to change or vary.
Example: The effect of socioeconomic status on
health.
SES
Health
(cause)
(effect)
Variables and Attributes
Example:
Types of Variables

Independent and Dependent
Independent
Dependent

Intervening Variables
Types of Variables

Antecedent variable
Attributes

Variables are sets of related values or attributes.
Hypotheses




Probability statements testing the relationships between or
among variables.
There are two types of statements: null or research (alternative
or hypothesis of interest)
Null means no relationship.]
Example: There is no relationship between SES and health.
Research (alternative or hypothesis of interest) states that there is
a relationship.
Example: There is a positive relationship between SES and
health, i.e., people with high SES are more likely to have better
health.
Theories

Explain why things are by linking cause and
effect.



Specify the circumstances or conditions under
which things happen.
Permit us to predict events.
Generally, we do not test theories; theories are
comprised of a number of hypotheses which are
then tested as parts of a theory.
Relationship Between Theory and
Research

Theories function three ways in research:
1.
2.
3.
They prevent our being taken in by flukes.
They can shape and direct research efforts.
They makes sense of observed patterns.
Units of Analysis

Units of analysis are the what or whom being
studied. In social science research there are
four types of units of analysis:
1. Individual people
Units of Analysis
2.
Groups (e.g., families or households)
4. Artifacts (e.g., paintings, books).
3. Organizations (e.g., universities in
Mclean’s polls);
Time Dimension
Cross-sectional Studies – based on observations made
during a single time period.
Longitudinal Studies – involve observations at two or
more time periods.
1.
2.
a)
b)
c)
Trend studies – study changes within some general
population over time.
Cohort studies – examine more specific subpopulations
(cohorts) as they change over time.
Panel studies -- similar to trend and cohort studies except
that the same set of people is studied each time.
Qualitative and Quantitative


Qualitative analysis is the nonnumerical
examination and interpretation of observations,
for the purpose of discovering underlying
meanings and patterns of relationships.
Quantitative analysis is the numerical
representation and manipulation of
observations for the purpose of describing and
explaining the phenomena that those
observations reflect.
Qualitative and Quantitative
Qualitative and Quantitative
Relationship Between Research
Topic, Theory and Data Collection
The research topic could influence the
theoretical perspective and the type of data
collection.
 It is also possible that the theoretical perspective
could influence the research methods or data
collection techniques.
Question: How would one study socialization of
children in the family?

Data Collection or Observation





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Surveys
Field Research
Content Analysis
Experiments
Comparative Historical Methods
Analysis of Existing Statistics (Secondary Data
Analysis)
Conceptualization and Measurement


Conceptualization refers to nominal definitions
(e.g., what is meant by better health or SES?)
Operationalization refers to measurement of the
variables (e.g., how do you measure better health
or SES?)
Validity and Reliability

There are two criteria in measurements:
Validity – a term describing a measure that
accurately reflects the concept it is intended to
measure.
2. Reliability – the degree to which a research
instrument, such as a questionnaire or a coding
system, produces consistent results with use.
Example: Are students’ grade point averages a valid
and reliable measure of their intelligence?
1.
Operationalization (measurement)

Every variable must have two important
qualities:
1.
2.
The attributes should be exhaustive. We must be
able to classify every observation in terms of one
of the attributes. (e.g., political party affiliation in
Nova Scotia: Liberal, PC, NDP, other)
They must be mutually-exclusive. Every
observation must be able to be classified in terms
of one and only one attribute. (e.g., income:
under 5000; 5000-10,000; over 10,000)
Levels of Measurement
There are four levels of
measurement of variables:

1.
Nominal – variables whose
attributes have only the
characteristics of
exhaustiveness and mutuallyexclusiveness, e.g., gender.
2.
Ordinal – variables with
attributes that are logically
rank-ordered, e.g., SES –
low, middle, high.
Levels of Measurement
3.
Interval – the distance between
attributes can be expressed in
meaningful standard intervals, e.g.,
temperature.
4.
Ratio – variables having all the above
requirements plus are based on a true
zero point, e.g., income.
Question: What are the advantages of measuring income as an ordinal measure versus
a ratio measure?
Multiple Indicators



Some variables are better measured (greater
validity and reliability) using multiple indicators.
For example, liberalism.
We can combine indicators to form indexes and
scales. For example, job satisfaction.
Indexes and scales are both ordinal measures.
Indexes

An index is constructed by simply adding
scores assigned to individual attributes, e.g., we
might measure prejudice by adding up the
number of statements each respondent agreed
with.
Indexes
Scales

A scale is constructed by assigning scores to patterns of
responses. Some items reflect a relatively weak degree
of the variable, while others reflect something stronger.
For example, women are different from men (weak
degree of sexism); women should not be allowed to
vote (stronger evidence of sexism). A scale has an
intensity structure among the attributes.
Scales
Ethics
Ethical obligations to respondents:

1.
Voluntary participation and consent

2.
Statements informing participants about the goals of the study and
consent forms would need to be prepared in advance.
The right to privacy, the maintenance of dignity and
protection against harm.

Anonymity and confidentiality
Question: What effects could the above have on the
research in terms of, for example, reliability?
Quantitative Data Analysis

Univariate Analysis

Central tendency
(averages)
•
•
•
Mode (most frequent
number)
Mean (arithmetic average)
Median (midpoint)
Quantitative Data Analysis
Quantitative Data Analysis

Dispersion
Range (from highest to lowest)
 Standard deviation

Quantitative Data Analysis

Bivariate Analysis

Looking for relationships between two variables.
Independent
(e.g., gender)
Dependent
(e.g., attitude toward
legalization of marijuana)
Quantitative Data Analysis

Constructing and reading bivariate tables
•
•
Tables should have a title and number
The independent variable should be at the top; the
dependent variable at the side.
NOTE: Insert example of a table.
Quantitative Data Analysis

Multivariate Analysis and the Elaboration
Model

Multivariate analysis is the analysis of more than two
variables simultaneously.
Quantitative Data Analysis
The Elaboration Paradigm
Quantitative Data Analysis
Elaboration Model

1.
2.
3.
Replication is when the partial relationships are essentially
the same as the original relationship.
Interpretation is when the original relationship is
significantly weakened or disappears as a result of an
intervening variable.
Explanation is used to describe a spurious relationship,
i.e., an original relationship shown to be false through the
introduction of an antecedent test variable. An antecedent
variable is one that precedes both the independent and
dependent variables.
Quantitative Data Analysis

Refinements to the Elaboration Model
A suppressor variable affects the relationship
between the independent and dependent variable
such that no relationship seems to exist. However,
when controlling for the suppressor variable, the
relationship between the independent and dependent
variable appears.
 A distorter variable reverses the true relationship
between the independent and dependent variables.
